Skip to main content

Inductive Synthesis of the Models of Biological Systems According to Clinical Trials

  • Conference paper
  • First Online:
Computational Science and Its Applications – ICCSA 2017 (ICCSA 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10404))

Included in the following conference series:

Abstract

In the article an approach to solving the problem of inductive synthesis of the models of biological systems according to clinical trials is suggested. Suggested approach to inductive synthesis of biological models on the base of results of clinical trials allows essentially decrease computational complexity of this problem. Formalization of biological models in the form of graph of parameters allows use well developed mathematical apparatus of theory of graphs, which suggest effective methods of models transformation. Nowadays suggested approach is used in Almazov Cardiological Center for automatic medical data processing.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Lushnov, A., Lushnov, M.: Medical Information Systems: Multidimensional Analyses of Medical and Ecology Data. Helicon Plus, SpB (2013)

    Google Scholar 

  2. Kupershtoh, V., Mirkin, B., Trofimov, V.: The sum of internal links as indicator of classification results quality. Avtomatika i Telemekhanika 3, 133–141 (1976). (in Russian)

    Google Scholar 

  3. Kriete, A., Eils, R.: Computational Systems Biology. Elsevier Academic Press, Cambridge (2006)

    Google Scholar 

  4. Akbari, Z., Unland, R.: Automated determination of the input parameter of DBSCAN based on outlier detection. In: Iliadis, L., Maglogiannis, I. (eds.) AIAI 2016. IFIP AICT, vol. 475, pp. 280–291. Springer, Cham (2016). doi:10.1007/978-3-319-44944-9_24

    Chapter  Google Scholar 

  5. Stankova, E.N., Balakshiy, A.V., Petrov, D.A., Shorov, A.V., Korkhov, V.V.: Using technologies of OLAP and machine learning for validation of the numerical models of convective clouds. In: Gervasi, O., et al. (eds.) ICCSA 2016, Part III. LNCS, vol. 9788, pp. 463–472. Springer, Cham (2016). doi:10.1007/978-3-319-42111-7_36

    Chapter  Google Scholar 

  6. Raba, N.O., Stankova, E.N.: On the problem of numerical modeling of dangerous convective phenomena: possibilities of real-time forecast with the help of multi-core processors. In: Murgante, B., Gervasi, O., Iglesias, A., Taniar, D., Apduhan, B.O. (eds.) ICCSA 2011. LNCS, vol. 6786, pp. 633–642. Springer, Heidelberg (2011). doi:10.1007/978-3-642-21934-4_51

    Chapter  Google Scholar 

  7. Freedman, D.: Statistical Models: Theory and Practice, 2nd edn. Cambridge University Press, Cambridge (2009)

    Book  MATH  Google Scholar 

  8. Gill, P.R., Murray, W., Wright, M.H.: The Levenberg-Marquardt method. In: Practical Optimization, pp. 136–137. Academic Press, London (1981)

    Google Scholar 

  9. Zaki, M.J., Meira Jr., W.: Data Mining and Analysis: Fundamental Concepts and Algorithms. Cambridge University Press, Cambridge (2014)

    MATH  Google Scholar 

  10. Feldman, R., Sanger, J.: The Text Mining Handbook: Advanced Approaches in Analyzing Unstructured Data. Cambridge University Press, Cambridge (2006)

    Book  Google Scholar 

  11. Leskovec, J., Rajaraman, A., Ullman, J.: Mining Massive Datasets. Stanford University, Stanford (2014)

    Book  Google Scholar 

Download references

Acknowledgement

This work was partially financially supported by Government of Russian Federation, Grant 074-U01

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Nataly Zukova .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Osipov, V., Lushnov, M., Stankova, E., Vodyaho, A., Zukova, N. (2017). Inductive Synthesis of the Models of Biological Systems According to Clinical Trials. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2017. ICCSA 2017. Lecture Notes in Computer Science(), vol 10404. Springer, Cham. https://doi.org/10.1007/978-3-319-62392-4_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-62392-4_8

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-62391-7

  • Online ISBN: 978-3-319-62392-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics